245 resultados para Partial identification


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Fruit flies that belong to the genus Bactrocera (Diptera: Tephritidae) are major invasive pests of agricultural crops in Asia and Australia. Increased transboundary movement of agricultural produce has resulted in the chance introduction of many invasive species that include Bactrocera mainly as immature stages. Therefore quick and accurate species diagnosis is important at the port of entry, where morphological identification has a limited role, as it requires the presence of adult specimens and the availability of a specialist. Unfortunately when only immature stages are present, a lacunae in their taxonomy impedes accurate species diagnosis. At this juncture, molecular species diagnostics based on COX-I have become handy, because diagnosis is not limited by developmental stages. Yet another method of quick and accurate species diagnosis for Bactrocera spp. is based on the development of species-specific markers. This study evaluated the utility of COX-I for the quick and accurate species diagnosis of eggs, larvae, pupae and adults of B. zonata Saunders, B. tau Walker, and B. dorsalis Hendel. Furthermore the utility of species-specific markers in differentiating B. zonata (500bp) and B. tau (220bp) was shown. Phylogenetic relationships among five subgenera, viz., Austrodacus, Bactrocera, Daculus, Notodacus and Zeugodacus have been resolved employing the 5' region of COX-I (1490-2198); where COX-I sequences for B. dorsalis Hendel, B. tau Walker, B. correcta Bezzi and B. zonata Saunders from India were compared with other NCBI-GenBank accessions. Phylogenetic analysis employing Maximum Parsimony (MP) and Bayesian phylogenetic approach (BP) showed that the subgenus Bactrocera is monophyletic.

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Parallel sub-word recognition (PSWR) is a new model that has been proposed for language identification (LID) which does not need elaborate phonetic labeling of the speech data in a foreign language. The new approach performs a front-end tokenization in terms of sub-word units which are designed by automatic segmentation, segment clustering and segment HMM modeling. We develop PSWR based LID in a framework similar to the parallel phone recognition (PPR) approach in the literature. This includes a front-end tokenizer and a back-end language model, for each language to be identified. Considering various combinations of the statistical evaluation scores, it is found that PSWR can perform as well as PPR, even with broad acoustic sub-word tokenization, thus making it an efficient alternative to the PPR system.

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Frequent episode discovery is a popular framework for temporal pattern discovery in event streams. An episode is a partially ordered set of nodes with each node associated with an event type. Currently algorithms exist for episode discovery only when the associated partial order is total order (serial episode) or trivial (parallel episode). In this paper, we propose efficient algorithms for discovering frequent episodes with unrestricted partial orders when the associated event-types are unique. These algorithms can be easily specialized to discover only serial or parallel episodes. Also, the algorithms are flexible enough to be specialized for mining in the space of certain interesting subclasses of partial orders. We point out that frequency alone is not a sufficient measure of interestingness in the context of partial order mining. We propose a new interestingness measure for episodes with unrestricted partial orders which, when used along with frequency, results in an efficient scheme of data mining. Simulations are presented to demonstrate the effectiveness of our algorithms.

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This paper proposes a new approach for solving the state estimation problem. The approach is aimed at producing a robust estimator that rejects bad data, even if they are associated with leverage-point measurements. This is achieved by solving a sequence of Linear Programming (LP) problems. Optimization is carried via a new algorithm which is a combination of “upper bound optimization technique" and “an improved algorithm for discrete linear approximation". In this formulation of the LP problem, in addition to the constraints corresponding to the measurement set, constraints corresponding to bounds of state variables are also involved, which enables the LP problem more efficient in rejecting bad data, even if they are associated with leverage-point measurements. Results of the proposed estimator on IEEE 39-bus system and a 24-bus EHV equivalent system of the southern Indian grid are presented for illustrative purpose.

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The search for molecular markers which predict response to chemotherapy is an important aspect of current neuro-oncology research. MGMT promoter methylation is the only proved marker of glioblastoma. The purpose of this study was to assess the effect of topoisomerase expression on glioblastoma survival and study the mechanisms involved. The transcript levels of all isoforms of the topoisomerase family in all grades of diffuse astrocytoma were assessed. A prospective study of patients with glioblastoma treated by a uniform treatment procedure was performed with the objective of correlating outcome with gene expression. The ability of TOP2A enzyme to relax the super coiled plasmid DNA in the presence of temozolomide was evaluated to assess its effect on TOP2A. The temozolomide cyctotoxicity of TOP2A-silenced U251 cells was assessed. The transcript levels of TOP2A, TOP2B, and TOP3A are upregulated significantly in GBM in comparison with lower grades of astrocytoma and normal brain samples. mRNA levels of TOP2A correlated significantly with survival of the patients. Higher TOP2A transcript levels in GBM patients predicted better prognosis (P = 0.043; HR = 0.889). Interestingly, we noted that temozolomide inhibited TOP2A activity in in-vitro enzyme assays. We also noted that siRNA knock down of TOP2A rendered a glioma cell line resistant to temozolomide chemotherapy. We demonstrated for the first time that temozolomide is also a TOP2A inhibitor and established that TOP2A transcript levels determine the chemosensitivity of glioblastoma to temozolomide therapy. Very high levels of TOP2A are a good prognostic indicator in GBM patients receiving temozolomide chemotherapy.

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We report gas phase mid-infrared spectra of 1- and 2- methyl naphthalenes at 0.2 cm(-1) resolution. Assignment of observed bands have been made using scaled quantum mechanical (SQM) calculations where the force fields rather the frequencies are scaled to find a close fit between observed and calculated bands. The structure of the molecules has been optimized using B3LYP level of theory in conjunction with standard 6-311G** basis set to obtain the harmonic frequencies. Using the force constants in Cartesian coordinates from the Gaussian output, scaled force field calculations are carried out using a modified version of the UMAT program in the QCPE package. Potential energy distributions of the normal modes obtained from such calculations helped us assign the observed bands and identify the unique features of the spectra of 1- and 2-MNs which are important for their isomeric identification.

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A method for the estimation of vapour pressure and partial pressure of subliming compounds under reduced pressure, using rising temperature thermogravimetry, is described in this paper. The method is based on our recently developed procedure to estimate the vapour pressure from ambient pressure thermogravimetric data using Langmuir equation. Using benzoic acid as the calibration standard, vapour pressure temperature curves are calculated at 80, 160 and 1000 mbar for salicylic acid and vanadyl bis-2,4-pentanedionate, a precursor used for chemical vapour deposition of vanadium oxides. Using a modification of the Langmuir equation, the partial pressure of these materials at different total pressures is also determined as a function of temperature. Such data can be useful for the deposition of multi-metal oxide thin films or doped thin films by chemical vapour deposition (CVD).

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A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative `Connect to Decode' (C2D) to generate the first and largest manually curated interactome of Mtb termed `3interactome pathway' (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.

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Acetaminophen is a widely prescribed drug used to relieve pain and fever; however, it is a leading cause of drug-induced liver injury and a burden on public healthcare. In this study, hepatotoxicity in mice post oral dosing of acetaminophen was investigated using liver and sera samples with Fourier Transform Infrared microspectroscopy. The infrared spectra of acetaminophen treated livers in BALB/ mice show decrease in glycogen, increase in amounts of cholesteryl esters and DNA respectively. Rescue experiments using L-methionine demonstrate that depletion in glycogen and increase in DNA are abrogated with pre-treatment, but not post-treatment, with L-methionine. This indicates that changes in glycogen and DNA are more sensitive to the rapid depletion of glutathione. Importantly, analysis of sera identified lowering of glycogen and increase in DNA and chlolesteryl esters earlier than increase in alanine aminotransferase, which is routinely used to diagnose liver damage. In addition, these changes are also observed in C57BL/6 and Nos2(-/-) mice. There is no difference in the kinetics of expression of these three molecules in both strains of mice, the extent of damage is similar and corroborated with ALT and histological analysis. Quantification of cytokines in sera showed increase upon APAP treatment. Although the levels of Tnf alpha and Ifn gamma in sera are not significantly affected, Nos2(-/-) mice display lower Il6 but higher Il10 levels during this acute model of hepatotoxicity. Overall, this study reinforces the growing potential of Fourier Transform Infrared microspectroscopy as a fast, highly sensitive and label-free technique for non-invasive diagnosis of liver damage. The combination of Fourier Transform Infrared microspectroscopy and cytokine analysis is a powerful tool to identify multiple biomarkers, understand differential host responses and evaluate therapeutic regimens during liver damage and, possibly, other diseases.

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Background: Bacteria such as Escherichia coli and Salmonella typhimurium can utilize acetate as the sole source of carbon and energy. Acetate kinase (AckA) and phosphotransacetylase (Pta), key enzymes of acetate utilization pathway, regulate flux of metabolites in glycolysis, gluconeogenesis, TCA cycle, glyoxylate bypass and fatty acid metabolism. Results: Here we report kinetic characterization of S. typhimurium AckA (StAckA) and structures of its unliganded (Form-I, 2.70 angstrom resolution) and citrate-bound (Form-II, 1.90 angstrom resolution) forms. The enzyme showed broad substrate specificity with k(cat)/K-m in the order of acetate > propionate > formate. Further, the K-m for acetyl-phosphate was significantly lower than for acetate and the enzyme could catalyze the reverse reaction (i.e. ATP synthesis) more efficiently. ATP and Mg2+ could be substituted by other nucleoside 5'-triphosphates (GTP, UTP and CTP) and divalent cations (Mn2+ and Co2+), respectively. Form-I StAckA represents the first structural report of an unliganded AckA. StAckA protomer consists of two domains with characteristic beta beta beta alpha beta alpha beta alpha topology of ASKHA superfamily of proteins. These domains adopt an intermediate conformation compared to that of open and closed forms of ligand-bound Methanosarcina thermophila AckA (MtAckA). Spectroscopic and structural analyses of StAckA further suggested occurrence of inter-domain motion upon ligand-binding. Unexpectedly, Form-II StAckA structure showed a drastic change in the conformation of residues 230-300 compared to that of Form-I. Further investigation revealed electron density corresponding to a citrate molecule in a pocket located at the dimeric interface of Form-II StAckA. Interestingly, a similar dimeric interface pocket lined with largely conserved residues could be identified in Form-I StAckA as well as in other enzymes homologous to AckA suggesting that ligand binding at this pocket may influence the function of these enzymes. Conclusions: The biochemical and structural characterization of StAckA reported here provides insights into the biochemical specificity, overall fold, thermal stability, molecular basis of ligand binding and inter-domain motion in AckA family of enzymes. Dramatic conformational differences observed between unliganded and citrate-bound forms of StAckA led to identification of a putative ligand-binding pocket at the dimeric interface of StAckA with implications for enzymatic function.

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A newly implemented G-matrix Fourier transform (GFT) (4,3)D HC(C)CH experiment is presented in conjunction with (4,3)D HCCH to efficiently identify H-1/C-13 sugar spin systems in C-13 labeled nucleic acids. This experiment enables rapid collection of highly resolved relay 4D HC(C)CH spectral information, that is, shift correlations of C-13-H-1 groups separated by two carbon bonds. For RNA, (4,3)D HC(C)CH takes advantage of the comparably favorable 1'- and 3'-CH signal dispersion for complete spin system identification including 5'-CH. The (4,3)D HC(C)CH/HCCH based strategy is exemplified for the 30-nucleotide 3'-untranslated region of the pre-mRNA of human U1A protein.

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Phase equilibria in the system Tm-Rh-O at 1200 K is established by isothermal equilibration of selected compositions and phase identification after quenching to room temperature. Six intermetallic phases (Tm3Rh, Tm7Rh3, Tm5Rh3, Tm3Rh2, TmRh, TmRh2 +/-delta) and a ternary oxide TmRhO3 are identified. Based on experimentally determined phase relations, a solid-state electrochemical cell is devised to measure the standard free energy of formation of orthorhombic perovskite TmRhO3 from cubic Tm2O3 and beta-Rh2O3 in the temperature range from (900 to 1300) K. The results can be summarized as: Delta G(f,ox)(o) +/- 104/J.mol(-1) = -46474 + 3.925(T/K). Invoking the Neumann-Kopp rule, the standard enthalpy of formation of TmRhO3 from its constituent elements at 298.15 K is estimated as -1193.89 (+/- 2.86) kJ.mol(-1). The standard entropy of TmRhO3 at 298.15 K is evaluated as 103.8 (+/- 1.6) J.mol(-1).K-1. The oxygen potential-composition diagram and three-dimensional chemical potential diagram at 1200 K and temperature-composition diagrams at constant partial pressures of oxygen are computed from thermodynamic data. The compound TmRhO3 decomposes at 1688 (+/- 2) K in pure oxygen and at 1583 (+/- 2) K in air at standard pressure.

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We address the problem of identifying the constituent sources in a single-sensor mixture signal consisting of contributions from multiple simultaneously active sources. We propose a generic framework for mixture signal analysis based on a latent variable approach. The basic idea of the approach is to detect known sources represented as stochastic models, in a single-channel mixture signal without performing signal separation. A given mixture signal is modeled as a convex combination of known source models and the weights of the models are estimated using the mixture signal. We show experimentally that these weights indicate the presence/absence of the respective sources. The performance of the proposed approach is illustrated through mixture speech data in a reverberant enclosure. For the task of identifying the constituent speakers using data from a single microphone, the proposed approach is able to identify the dominant source with up to 8 simultaneously active background sources in a room with RT60 = 250 ms, using models obtained from clean speech data for a Source to Interference Ratio (SIR) greater than 2 dB.